Python Materials Genomics is a robust materials analysis code that defines core object representations for structures and molecules with support for many electronic structure codes. It is currently the core analysis code powering the Materials Project (https://www.materialsproject.org).

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for janosh from gravatar.com janosh Avatar for mkhorton from gravatar.com mkhorton Avatar for Shyue.Ping.Ong from gravatar.com Shyue.Ping.Ong

Unverified details

These details have not been verified by PyPI
Project links
Meta
Classifiers

Project description

Official docs: https://pymatgen.org

Pymatgen (Python Materials Genomics) is a robust, open-source Python library for materials analysis. These are some of the main features:

  1. Highly flexible classes for the representation of Element, Site, Molecule, Structure objects.
  2. Extensive input/output support, including support for VASP, ABINIT, CIF, Gaussian, XYZ, and many other file formats.
  3. Powerful analysis tools, including generation of phase diagrams, Pourbaix diagrams, diffusion analyses, reactions, etc.
  4. Electronic structure analyses, such as density of states and band structure.
  5. Integration with the Materials Project REST API.

Pymatgen is free to use. However, we also welcome your help to improve this library by making your own contributions. These contributions can be in the form of additional tools or modules you develop, or feature requests and bug reports. Please report any bugs and issues at pymatgen's [Github page] (https://github.com/materialsproject/pymatgen). For help with any pymatgen issues, please use the Discourse page.

Why use pymatgen?

There are many materials analysis codes out there, both commerical and free, but pymatgen offer several advantages:

  1. It is (fairly) robust. Pymatgen is used by thousands of researchers, and is the analysis code powering the Materials Project. The analysis it produces survives rigorous scrutiny every single day. Bugs tend to be found and corrected quickly. Pymatgen also uses CircleCI and Appveyor for continuous integration on the Linux and Windows platforms, respectively, which ensures that every commit passes a comprehensive suite of unittests.
  2. It is well documented. A fairly comprehensive documentation has been written to help you get to grips with it quickly.
  3. It is open. You are free to use and contribute to pymatgen. It also means that pymatgen is continuously being improved. We will attribute any code you contribute to any publication you specify. Contributing to pymatgen means your research becomes more visible, which translates to greater impact.
  4. It is fast. Many of the core numerical methods in pymatgen have been optimized by vectorizing in numpy/scipy. This means that coordinate manipulations are extremely fast and are in fact comparable to codes written in other languages. Pymatgen also comes with a complete system for handling periodic boundary conditions.
  5. It will be around. Pymatgen is not a pet research project. It is used in the well-established Materials Project. It is also actively being developed and maintained by the Materials Virtual Lab, the ABINIT group and many other research groups.

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for janosh from gravatar.com janosh Avatar for mkhorton from gravatar.com mkhorton Avatar for Shyue.Ping.Ong from gravatar.com Shyue.Ping.Ong

Unverified details

These details have not been verified by PyPI
Project links
Meta
Classifiers

Release history Release notifications | RSS feed

2024.11.13

2024.10.29

2024.10.27

2024.10.25

2024.10.22

2024.10.3

2024.9.17.1

2024.9.17

2024.9.10

2024.8.9

2024.8.8 yanked

Reason this release was yanked:

Backward incompatible change introduced.

2024.7.18

2024.6.10

2024.6.4

2024.5.31 yanked

2024.5.1

2024.4.13

2024.4.12

2024.3.1

2024.2.23

2024.2.20

2024.2.8

2024.1.27

2024.1.26

2023.12.18

2023.11.12

2023.11.10

2023.10.11

2023.10.4

2023.10.3

2023.9.25

2023.9.10

2023.9.2

2023.8.10

2023.7.20

2023.7.17

2023.7.14

2023.7.11

2023.6.28 yanked

Reason this release was yanked:

Bad release without wheels for some systems.

2023.6.23

2023.5.31

2023.5.10

2023.5.8

2023.3.23

2023.3.10

2023.2.28

2023.2.22

2023.1.30

2023.1.20

2023.1.9

2022.11.7

2022.11.1

2022.10.22

2022.9.21

2022.9.8

2022.8.23

2022.7.25

2022.7.24.1

2022.7.24 yanked

Reason this release was yanked:

remove defunct MPRester2 in favor of more streamlined handling of new and legacy API

2022.7.19

2022.7.8

2022.5.26

2022.5.19

This version

2022.5.18.1

2022.5.18

2022.5.17

2022.4.26

2022.4.19

2022.3.29

2022.3.24

2022.3.22

2022.3.7

2022.2.10

2022.2.7

2022.2.1

2022.1.24

2022.1.20

2022.1.9

2022.1.8

2022.0.17

2022.0.16

2022.0.15

2022.0.14

2022.0.13

2022.0.12

2022.0.11

2022.0.10

2022.0.9

2022.0.8

2022.0.7

2022.0.6

2022.0.5

2022.0.4

2022.0.3

2022.0.2 yanked

Reason this release was yanked:

Buggy version

2022.0.1 yanked

Reason this release was yanked:

Buggy version

2022.0.0 yanked

Reason this release was yanked:

Buggy version

2021.3.9

2021.3.5

2021.3.4 yanked

Reason this release was yanked:

Breaking change in this version. Reverted in 2021.3.5.

2021.3.3

2021.2.16

2021.2.14

2021.2.13

2021.2.8.1

2021.2.8

2020.12.31

2020.12.18

2020.12.3

2020.11.11

2020.10.20

2020.10.9.1

2020.10.9

2020.9.14

2020.8.13

2020.8.3

2020.7.18

2020.7.16

2020.7.14

2020.7.10

2020.7.3

2020.6.8

2020.4.29

2020.4.2

2020.3.13

2020.3.2

2020.1.28

2020.1.10

2019.12.22

2019.12.3

2019.11.11

2019.10.16

2019.10.4

2019.10.3

2019.10.2

2019.9.16

2019.9.12

2019.9.8

2019.9.7

2019.8.23

2019.8.14

2019.7.30

2019.7.21

2019.7.2

2019.6.20

2019.6.5

2019.5.28

2019.5.8

2019.5.1

2019.4.11

2019.3.27

2019.3.13

2019.2.28

2019.2.24

2019.2.4

2019.1.24

2019.1.13

2018.12.12

2018.11.30

2018.11.6

2018.10.18

2018.9.30

2018.9.19

2018.9.12

2018.9.1

2018.8.10

2018.8.7

2018.7.23

2018.7.15

2018.6.27

2018.6.11

2018.5.22

2018.5.21

2018.5.14

2018.5.3

2018.4.20

2018.4.6

2018.3.23

2018.3.14

2018.3.13

2018.3.2

2018.2.13

2018.1.29

2018.1.19

2017.12.30

2017.12.16

2017.12.15

2017.12.8

2017.12.6

2017.11.30

2017.11.27

2017.11.9

2017.11.6

2017.10.16

2017.9.23

2017.9.3

2017.9.1

2017.8.21

2017.8.20

2017.8.16

2017.8.14

2017.8.4

2017.7.21

2017.7.4

2017.6.24

2017.6.22

2017.6.8

4.7.7

4.7.6

4.7.5

4.7.4

4.7.3

4.7.2

4.7.1

4.7.0

4.6.2

4.6.1

4.6.0

4.5.7

4.5.6

4.5.5

4.5.4

4.5.3

4.5.2

4.5.1

4.5.0

4.4.12

4.4.11

4.4.10

4.4.9

4.4.8

4.4.7

4.4.6

4.4.5

4.4.4

4.4.3

4.4.2

4.4.1

4.4.0

4.3.2

4.3.1

4.3.0

4.2.5

4.2.4

4.2.3

4.2.2

4.2.1

4.2.0

4.1.1

4.1.0

4.0.2

4.0.1

4.0.0

3.7.1

3.7.0

3.6.1

3.6.0

3.5.3

3.5.2

3.5.1

3.5.0

3.4.0

3.3.6

3.3.5

3.3.4

3.3.3

3.3.2

3.3.1

3.3.0

3.2.10

3.2.9

3.2.8

3.2.7

3.2.6

3.2.5

3.2.4

3.2.3

3.2.2

3.2.1

3.2.0

3.1.9

3.1.8

3.1.7

3.1.6

3.1.5

3.1.4

3.1.3

3.1.2

3.1.1

3.1.0

3.0.13

3.0.12

3.0.11

3.0.10

3.0.9

3.0.8

3.0.7

3.0.6

3.0.5

3.0.4

3.0.3

3.0.2

3.0.1

3.0.0

2.10.6

2.10.5

2.10.4

2.10.3

2.10.2

2.10.1

2.10.0

2.9.14

2.9.13

2.9.12

2.9.11

2.9.10

2.9.9

2.9.8

2.9.7

2.9.6

2.9.5

2.9.4

2.9.3

2.9.2

2.9.1

2.9.0

2.8.10

2.8.9

2.8.8

2.8.7

2.8.6

2.8.5

2.8.3

2.8.2

2.8.1

2.8.0

2.7.9

2.7.8

2.7.7

2.7.6

2.7.5

2.7.4

2.7.3

2.7.2b pre-release

2.7.1

2.7.0

2.6.6

2.6.5

2.6.4

2.6.3

2.6.2

2.6.1

2.5.5

2.5.4

2.5.3

2.5.2

2.5.1

2.5.0

2.4.3

2.4.2

2.4.1

2.4.0

2.3.2

2.3.1

2.3.0

2.2.6

2.2.4

2.2.3

2.2.2

2.2.1

2.2.0

2.1.2

2.1.0

2.0.0

1.9.0

1.8.3

1.8.2

1.8.0

1.7.2

1.7.0

1.6.0

1.5.0

1.2.9

1.2.8

1.2.4

1.2.3

1.2.2

1.2.1

1.2.0

1.1.2

1.1.1

1.1.0

1.0.5

1.0.4

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pymatgen-2022.5.18.1.tar.gz (2.6 MB view details)

Uploaded Source

Built Distributions

pymatgen-2022.5.18.1-cp310-cp310-win_amd64.whl (3.1 MB view details)

Uploaded CPython 3.10 Windows x86-64

pymatgen-2022.5.18.1-cp310-cp310-macosx_10_15_x86_64.whl (3.1 MB view details)

Uploaded CPython 3.10 macOS 10.15+ x86-64

pymatgen-2022.5.18.1-cp39-cp39-win_amd64.whl (3.1 MB view details)

Uploaded CPython 3.9 Windows x86-64

pymatgen-2022.5.18.1-cp39-cp39-macosx_11_0_arm64.whl (3.1 MB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

pymatgen-2022.5.18.1-cp39-cp39-macosx_10_15_x86_64.whl (3.1 MB view details)

Uploaded CPython 3.9 macOS 10.15+ x86-64

pymatgen-2022.5.18.1-cp38-cp38-win_amd64.whl (3.1 MB view details)

Uploaded CPython 3.8 Windows x86-64

pymatgen-2022.5.18.1-cp38-cp38-macosx_10_15_x86_64.whl (3.1 MB view details)

Uploaded CPython 3.8 macOS 10.15+ x86-64

File details

Details for the file pymatgen-2022.5.18.1.tar.gz.

File metadata

  • Download URL: pymatgen-2022.5.18.1.tar.gz
  • Upload date:
  • Size: 2.6 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.0 CPython/3.9.12

File hashes

Hashes for pymatgen-2022.5.18.1.tar.gz
Algorithm Hash digest
SHA256 d4c1d236a21663f7caae3ff0164a3a9860d51c679fb58370a5d08bcca26dc3df
MD5 456b4e3b264f97f3b8df329577f8ec4c
BLAKE2b-256 38a4e2df7f0ba14ac3a980a0c9067301e846ccbeea83602de7075a3dec763b42

See more details on using hashes here.

File details

Details for the file pymatgen-2022.5.18.1-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for pymatgen-2022.5.18.1-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 0d78dc6b0a9cdb928ef0cc5053544a5180e83e61a567d9d0805e0d66cbe98cdc
MD5 f98d2478214cf692ce4c4a0f2ad74a14
BLAKE2b-256 a2aa44358cce277d2f77dcf676ce3ee85c58b7b74247029999c345bb4ee16b9e

See more details on using hashes here.

File details

Details for the file pymatgen-2022.5.18.1-cp310-cp310-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for pymatgen-2022.5.18.1-cp310-cp310-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 3d89815e8095df2d0bbf227766a098c8bcbdfb3660fb17d75f94a325894d4d8a
MD5 0229d6f60aff4688ba376b97545dc096
BLAKE2b-256 1bf5d28a83688161c2ff6c77c1aefad5b24aba3c5e4f8128dad28e55bf663aaa

See more details on using hashes here.

File details

Details for the file pymatgen-2022.5.18.1-cp39-cp39-win_amd64.whl.

File metadata

File hashes

Hashes for pymatgen-2022.5.18.1-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 e659fdb59eb295d88efa5a27de9b4a9f2e0ed23694f4fec1ef27bf3db6a0b146
MD5 44019c268c91db381b205df833ad4fc0
BLAKE2b-256 bd8438971810685ecc069ab3d17899315bfd8088d364764a76ce1c653879cff8

See more details on using hashes here.

File details

Details for the file pymatgen-2022.5.18.1-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pymatgen-2022.5.18.1-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 d222c6bc69b3123f6ddf700519bc74eddacb234a3c9a6f38f44da8f05f64ce84
MD5 ca868825dbd5875a06688c4c037b935c
BLAKE2b-256 d299e29a1d71ad54a39ac1fa5270e2bb4695eeb8bd9d89ac1916c206427a7ade

See more details on using hashes here.

File details

Details for the file pymatgen-2022.5.18.1-cp39-cp39-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for pymatgen-2022.5.18.1-cp39-cp39-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 3d3af613211af6778e122aa7608e29650fe1d38297b65c43e71aab6bfdcff2e7
MD5 c86614e2c5a06ece17e7b5e51bf659c5
BLAKE2b-256 f3a0d348d3969a7ee77ddc6114f93712f9af4355aa2633533a57a9ccb242e128

See more details on using hashes here.

File details

Details for the file pymatgen-2022.5.18.1-cp38-cp38-win_amd64.whl.

File metadata

File hashes

Hashes for pymatgen-2022.5.18.1-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 6915ecdb4bf03fc4d430a3b8d6a7ac71c59621f9830e5ec790af30b10c4ad3e2
MD5 41e32ed457bb8ea8839b4325042cb959
BLAKE2b-256 28fce0fb59998124502038dcec14f6c29b66d9c86e473e5644f57cf8ce5586d0

See more details on using hashes here.

File details

Details for the file pymatgen-2022.5.18.1-cp38-cp38-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for pymatgen-2022.5.18.1-cp38-cp38-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 e4c0dbdb7564433fdda3cde3eee0f59262ba911c6b286578f97f51f4365d4683
MD5 044e5489185c22ba0ab0df0be2bf1da6
BLAKE2b-256 cbc26afc96223399c21b86ea7b5b71d34f17d01fd57203d62bc03adffa5173da

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page